Load balancing of distributed services

ABSTRACT

Various embodiments load balance service requests across one or more servers. In one embodiment, a service requestor directly accesses a shared metrics array stored in at least one server of a plurality of servers in a service cluster. Each of these servers includes one or more services. The shared metrics array is accessible by each of the plurality of servers, and includes a set of metrics for each of the plurality of servers. A determination is made based on the set of metrics associated with at least one server in the plurality of servers if a service request is to be sent to the at least one server. The service request is sent to the at least one server based on determining that the service request is to be sent to the at least one sever.

BACKGROUND

The present disclosure generally relates to distributed services, andmore particularly relates to load balancing distributed services.

A service can be generally described as a set of softwarefunctionalities/capabilities that can be utilized for differentpurposes. These capabilities are accessed utilizing one or moreinterfaces according to a specification associated with the service.Many services such as internet or web-based services often requiremultiple callbacks to secondary services. Each of these services andsub-services are generally distributed across multiple web servers.Therefore, balancing of incoming requests is usually performed toguarantee fairness and efficiency while serving these requests.

Conventional load balances are generally live/active server processesthat act as proxy between the service requesters and servers hosting theservices. The requesters send their service requests to the loadbalancer(s) who then dispatches the requests to the appropriate servers.These conventional load balancers have numerous drawbacks. For example,the number of load balancers is usually fewer than the number of servicerequesters, which results in the load balancers becoming a bottleneck inthe system. The latency of a service call is at least doubled sinceconventional load balancers are usually situated in between requestersand the servers hosting the services. Also, since conventional loadbalancers are live processes they consume CPU time, memory, trashcaches, etc.

BRIEF SUMMARY

In one embodiment, a method for load balancing service requests acrossone or more servers is disclosed. The method comprises accessing, by aservice requestor, a shared metrics array stored in at least one serverof a plurality of servers in a service cluster. Each of the plurality ofservers comprises one or more services. The shared metrics array isdirectly accessed by the service requestor without involving a processorof the at least one server. The shared metrics array being accessible byeach of the plurality of servers, and comprises a set of metrics foreach of the plurality of servers. A determination is made based on theset of metrics associated with at least one server in the plurality ofservers if a service request is to be sent to the at least one server.The service request is sent to the at least one server based ondetermining that the service request is to be sent to the at least onesever.

In another embodiment, an information processing system for loadbalancing service requests across one or more servers is disclosed. Theinformation processing system comprises a processor and a memorycommunicatively coupled to the processor. A load balancer iscommunicatively coupled to the processor and the memory. The loadbalancer is configured to perform a method. The method comprisesaccessing, by the information processing system, a shared metrics arraystored in at least one server of a plurality of servers in a servicecluster. Each of these servers comprises one or more services. Theshared metrics array is directly accessed by the load balancer withoutinvolving a processor of the at least one server. The shared metricsarray being accessible by each of the plurality of servers, andcomprises a set of metrics for each of the plurality of servers. Adetermination is made based on the set of metrics associated with atleast one server in the plurality of servers if a service request is tobe sent to the at least one server. The service request is sent to theat least one server based on determining that the service request is tobe sent to the at least one sever.

In yet another embodiment, a computer program storage product for loadbalancing service requests across one or more servers is disclosed. Thecomputer program storage product comprises instructions configured toperform a method on an information system. The method comprisesaccessing, by the information processing system, a shared metrics arraystored in at least one server of a plurality of servers in a servicecluster. Each of these servers comprises one or more services. Theshared metrics array is directly accessed by the service requestorwithout involving a processor of the at least one server. The sharedmetrics array being accessible by each of the plurality of servers, andcomprises a set of metrics for each of the plurality of servers. Adetermination is made based on the set of metrics associated with atleast one server in the plurality of servers if a service request is tobe sent to the at least one server. The service request is sent to theat least one server based on determining that the service request is tobe sent to the at least one sever.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying figures where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, and which together with the detailed description below areincorporated in and form part of the specification, serve to furtherillustrate various embodiments and to explain various principles andadvantages all in accordance with the present disclosure, in which:

FIG. 1 is a block diagram illustrating one example of an operatingenvironment according to one embodiment of the present disclosure;

FIG. 2 is a block diagram illustrating one example of a shared metricsarray used for load balancing service requests according to oneembodiment of the present disclosure;

FIG. 3 is a transactional diagram illustrating one example of a servicerequestor load balancing service requests utilizing a shared metricsarray according to one embodiment of the present disclosure;

FIG. 4 is an operational flow diagram illustrating one example of aservice requestor load balancing service requests utilizing a sharedmetrics array according to one embodiment of the present disclosure; and

FIG. 5 is a block diagram illustrating one example of an informationprocessing system discovering services in a service-orientedenvironment.

DETAILED DESCRIPTION

FIG. 1 illustrates a general overview of one operating environment 100according to one embodiment of the present disclosure. In oneembodiment, the operating environment 100 comprises one or more servicerequestors 102 communicatively coupled to at least one service cluster104 via one or more networks 106. In this embodiment, the servicecluster 104 comprises a plurality of computing devices 108, 110, 112such as multiple servers that are communicatively coupled together via anetwork 113. Multiple services 114, 116, 118 are distributed across eachof the computing devices 108, 110, 112.

In one embodiment, the service requestor 102 is a computing device suchas (but not limited to) a server, personal computing device, and/or thelike. The service requestor 102 comprises, for example, a serviceregistry 120 and a server selection manager 122. The service registry120 identifies each of the services 114, 116, 118 provided/hosted byeach of the servers 108, 110, 112 in the cluster 104. The serviceregistry 120 and server selection manager 122 are discussed in greaterdetail below.

FIG. 1 further shows that at least one of the servers 108 in the cluster104 comprises a shared metrics array 124. The shared metrics array 124is maintained in a portion of memory/storage on the server 108 that isshared between each of the servers 108, 110, 112 in the cluster 104.Stated differently each of the servers 108, 110, 112 in the cluster 104can access the shared metrics array 124. In one embodiment, the sharedmetrics array 124 comprises various metrics 126 associated with each ofthe servers 108, 110, 112. These metrics 126 include any type of metricsthat allow a service requester 102 to identify and select a server tosatisfy a service request. Examples of metrics include (but are notlimited to) current server capacity, load/performance, I/O and/or memorypressure, service type affinity, global health status (includingtemperature sensors, disk SMART health, and/or the like. In oneembodiment, the shared metrics array 124 is stored within a portion ofmemory/storage 127 that is shared across at least a plurality of theservers 108, 110, 112 in the cluster 104.

FIG. 2 shows a more detailed example of the shared metrics array 124. Inthis example, the shared metrics array 124 comprises a plurality ofslots 202, 204, 206. Each slot is associated with one of the servers108, 110, 112 in the cluster 104. For example, Slot_1 is associated withServer_1, Slot_2 is associated with Server_2, and Slot_N is associatedwith Server_N. In one embodiment, only the server associated with agiven slot 202, 204, 206 can access and update the slot. Each slot 202,204, 206 comprises, for example, a unique identifier (ID) 208 thatidentifies the slot, a unique ID 210 identifying the server associatedwith the slot, one or more server metrics 212, 214 utilized by a servicerequestor for selecting a server, a timestamp 216 indicating when themetric data 212, 214 was last updated, and connection information 218 tothe server associated with the slot (e.g., IP:PORT) . The shared metricsarray 124, in one embodiment, also includes information identifying thesize of the array 124.

In one embodiment, each server 108, 110, 112 in the cluster 104comprises a metric updater 128, 129, 131 for updating the metrics 126associated with the server in the shared metrics array 124. The metricupdater 128, 129, 131 communicates with the sever 108 comprising theshared metrics array 124 to update the metrics data 126 within itsassociated slot 202, 204, 206. In one embodiment, the metric updater128, 129, 131 directly accesses the slot 202, 204, 206 associated withits server. In this embodiment, the metric updater 128, 129, 131directly updates the metric data 126. For example, the metric updater128, 129, 131 utilizes one or more hardware-accelerated remote directmemory access (RDMA) operations such as an RDMA write to directly updatethe metrics 126. However, in another embodiment, the metric updater 128,129, 131 sends an update request to the server 108 comprising the sharedmetrics array 124. In this embodiment, the update request comprises, forexample, the slot ID and/or the server ID, operation to be performed(e.g., update metric data, delete metric data, add metric data, etc.),and metric data 126. The server 108 utilizes the data within the updaterequest to identify the slot 202 204, 206 in the shared metrics array124 associated with the server that sent the request. The server 108then performs the requested operation on the metric data 126 within theidentified slot 202, 204, 206.

In one embodiment, the server selection manager 122 of the servicerequestor 102 and the shared metrics array 124 of the server 108 form adistributed load-balancer 130. This load-balancer 130 is advantageousover conventional load-balancers since it is distributed across theservice requestor 102 and at least one of the servers 108, 110, 112 inthe cluster 104. This configuration removes the conventionalintermediary device that usually comprises the load-balancer. Therefore,the load-balancer 130 of one or more embodiments consumes less computingresources and reduces latency in the operating environment 100.

Turning now to FIG. 3, a transactional diagram is provided illustratingone example of load-balancing service requests across the servers in thecluster 104. At T1, the service requestor 102 generates a servicerequest and/or receives a service request from one or more other servicerequestors. The server selection manager 122 of the load-balancer 130analyzes the service registry 120 to identify the servers 108, 110, 112comprising services 114, 116, 118 that can satisfy the service request,at T2. The server selection manager 122 then selects at least one of theidentified servers 108, 110, 112 to satisfy the request, at T3. Theserver selection manager 122 can utilize any type of selectionprocess/policy such as (but not limited to) round-robin, random, lowestCPU, highest bandwidth, etc.

Once a server is selected, the server selection manager 122 directlyaccesses the shared metrics array 124, at T4. In one embodiment, theserver selection manager 122 utilizes one or more hardware-acceleratedremote direct memory access (RDMA) operations to access the sharedmetrics array 124 and locate the slot 202, 204, 206 associated with theselected server(s). For example, using the server ID, the serverselection manager 122 computes the location of the server's metrics inthe shared metrics array 124 and performs an RDMA read operation. ThisRDMA read operation retrieves the metrics information using the computedlocation of the metrics and their size, usually defined as constant.

The server selection manager 122 analyzes the metric data 126 from theslot to determine if the service request should be sent to the selectedserver, at T5. In one embodiment, the choice of sending or not sendingthe request to the selected server is dependent on a user-defined,client-side load balancing policy. Such policies can use variousalgorithms such as round-robin, random pick, or a more complex algorithmthat uses part or all of the metrics to define the final choice.Examples of more complex algorithms are low average CPU load, lowaverage network bandwidth usage, lowest CPU load in a quorum of randomlychosen servers, or lowest network bandwidth usage in a quorum ofrandomly chosen servers. If the server selection manager 122 determinesthat the service request should be sent to the selected server, theserver selection manager 122 sends the service request to the selectedserver, at T6. In one embodiment, the connection information within theshared metrics array slot 202, 204, 206 associated with the server isutilized by the server selection manager 122 to send the service requestto the selected server.

It should be noted that, in another embodiment, the server selectionmanager 122 first accesses the shared metrics array 124 prior toselecting a server. For example, the server selection manager 122 canaccess one or more slots 202, 204, 206 in the array 124 and analyze themetric data 126 in these slots. The server selection manager 122 canthen select at least one server for receiving the service request basedon the analyzed metric data 126. As discussed above, the serverselection manager 122 can utilize any type of selection process/policysuch as (but not limited to) round-robin, random, lowest CPU, highestbandwidth, etc. It should be noted that the server selection manager 122can also utilize one or more selection processes to select one or moreof the slots 202, 204, 206.

As can be seen from the above discussion, one or more embodiments enablea service requestor to perform load balancing of service requests acrossone or more servers in a service cluster. The service requestor is ableto directly access a shared metrics array stored at one or more of theservers. Hardware-accelerated RDMA operations can be utilized for thisdirect access. The service requestor utilizes server metric informationstored within the shared metrics array to select a server for receivinga service request sent from the service requestor.

FIG. 4 is an operational flow diagram illustrating one example of aservice requestor load balancing service requests utilizing a sharedmetrics array. The operational flow diagram of FIG. 4 begins at step 402and flows directly to step 404. A load balancer 130 situated at aservice requestor 102, at step 404, accesses a shared metrics array 124stored in at least one server 108 of a plurality of servers in a servicecluster 104. Each of these servers 108, 110, 112 comprises one or moreservices 114, 116, 118. The shared metrics array 124 is accessible byeach of the plurality of servers, and comprises a set of metrics 126 foreach of the plurality of servers.

The load balancer 130, at step 406, analyzes a set of metrics 126associated with at least one server in the plurality of servers. Theload balancer 130, at step 408, makes a determination, based on the setof metrics 126 associated with at least one server in the plurality ofservers, if a service request is to be sent to the at least one server.If the result of this determination is positive, the load balancer 130,at step 410, sends the service request to the at least one server basedon determining that the service request is to be sent to the at leastone sever. The control flow exits at step 412. If the result of thedetermination is negative, the load balancer 130, at step 414, selects aset of metrics 126 associated with at least one additional server in theplurality of servers. The load balancer 130, at step 416, analyzes, theset of metrics 126 associated with at the at least one additionalserver. The load balancer 130 then repeats the flow discussed above withrespect to steps 406 to 412.

Referring now to FIG. 5, this figure is a block diagram illustrating aninformation processing system that can be utilized in embodiments of thepresent disclosure. The information processing system 502 is based upona suitably configured processing system adapted to implement one or moreembodiments of the present disclosure (e.g., the server 218, 220 of FIG.2). Any suitably configured processing system can be used as theinformation processing system 500 in embodiments of the presentdisclosure. The components of the information processing system 502 caninclude, but are not limited to, one or more processors or processingunits 504, a system memory 506, and a bus 508 that couples varioussystem components including the system memory 506 to the processor 504.

The bus 508 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Although not shown in FIG. 5, the main memory 506 includes the serviceregistry 120 and at least a portion of the load balancer 130 comprisingthe server selection manager 122. In another embodiment, at least theportion of the load balancer 130 comprising the server selection manager122 can reside within the processor 504, or be a separate hardwarecomponent.

The system memory 506 can also include computer system readable media inthe form of volatile memory, such as random access memory (RAM) 510and/or cache memory 512. The information processing system 502 canfurther include other removable/non-removable, volatile/non-volatilecomputer system storage media. By way of example only, a storage system514 can be provided for reading from and writing to a non-removable orremovable, non-volatile media such as one or more solid state disksand/or magnetic media (typically called a “hard drive”). A magnetic diskdrive for reading from and writing to a removable, non-volatile magneticdisk (e.g., a “floppy disk”), and an optical disk drive for reading fromor writing to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to the bus 508 by one or more data media interfaces.The memory 506 can include at least one program product having a set ofprogram modules that are configured to carry out the functions of anembodiment of the present disclosure.

Program/utility 516, having a set of program modules 518, may be storedin memory 506 by way of example, and not limitation, as well as anoperating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Program modules 518 generally carry out the functionsand/or methodologies of embodiments of the present disclosure.

The information processing system 502 can also communicate with one ormore external devices 520 such as a keyboard, a pointing device, adisplay 522, etc.; one or more devices that enable a user to interactwith the information processing system 502; and/or any devices (e.g.,network card, modem, etc.) that enable computer system/server 502 tocommunicate with one or more other computing devices. Such communicationcan occur via I/O interfaces 524. Still yet, the information processingsystem 502 can communicate with one or more networks such as a localarea network (LAN), a general wide area network (WAN), and/or a publicnetwork (e.g., the Internet) via network adapter 526. As depicted, thenetwork adapter 526 communicates with the other components ofinformation processing system 502 via the bus 508. Other hardware and/orsoftware components can also be used in conjunction with the informationprocessing system 502. Examples include, but are not limited to:microcode, device drivers, redundant processing units, external diskdrive arrays, RAID systems, tape drives, and data archival storagesystems.

As will be appreciated by one skilled in the art, aspects of the presentdisclosure may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present disclosure may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present disclosure have been discussed above withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems) and computer program products according to variousembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The description of the present disclosure has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The embodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method, with an information processing system,for load balancing service requests across one or more servers, themethod comprising: accessing, by the information processing system inresponse to obtaining a service request, a shared metrics array storedin memory of at least one server of a plurality of servers in a servicecluster, where the information processing system comprises the servicerequest and is external to the service cluster, and where each server inthe plurality of servers comprises at least one service for satisfyingthe service request, the shared metrics array being accessible at theserver by each of the plurality of servers, wherein the shared metricsarray comprises a set of metrics for each of the plurality of servers,and wherein each of the plurality of servers comprises one or moreservices, the shared metrics array being directly accessed in the memoryof the server by the information processing system without involving aprocessor of the at least one server; determining, based on the set ofmetrics associated with at least one server in the plurality of servers,if the service request is to be sent to the at least one server; andsending the service request to the at least one server based ondetermining that the service request is to be sent to the at least onesever.
 2. The method of claim 1, wherein the accessing comprises:performing one or more remote direct memory access operations on amemory of the at least one server comprising the shared metrics array.3. The method of claim 1, further comprising: selecting the at least oneserver based on one or more selection policies.
 4. The method of claim1, wherein the accessing comprises: identifying a portion of the sharedmetrics array associated with the at least one server; and analyzing theset of metrics associated with the at least one server.
 5. The method ofclaim 1, further comprising: based determining that the service requestis not to be sent to the at least one server; selecting at least oneadditional server from the plurality of servers; and sending the servicerequest to the at least one additional server based on the set ofmetrics associated with the at least one additional server.
 6. Themethod of claim 1, wherein the shared metrics array comprises aplurality of slots, wherein each slot in the plurality of slots isassociated with one of the plurality of servers and comprises the set ofmetrics for the one of the plurality of servers.
 7. The method of claim6, a given slot in the plurality of slots is updatable only by itsassociated server in the plurality of servers.
 8. The method of claim 6,wherein each slot in the plurality of slots further comprises at leastone of: a timestamp associated with a most recent update to set ofmetrics stored within the slot; an identifier associated with the serverassociated with the slot; and a set of connection information for theserver associated with the slot.
 9. An information processing system forload balancing service requests across one or more servers, theinformation processing system comprising: a processor; a memorycommunicatively coupled to the processor; and a load balancercommunicatively coupled to the processor and the memory, the loadbalancer configured to perform a method comprising: selecting, inresponse to generating a service request, at least one server of aplurality of servers in a service cluster for receiving the servicerequest, wherein each server in the plurality of servers comprises atleast one service for satisfying the service request; after selectingthe at least one server, accessing a shared metrics array stored inmemory of at least one server of the plurality of servers in a servicecluster, where the information processing system is external to theservice cluster and comprises service request, the shared metrics arraybeing accessible at the server by each of the plurality of servers,wherein the shared metrics array comprises a set of metrics for each ofthe plurality of servers, and wherein each of the plurality of serverscomprises one or more services, the shared metrics array being directlyaccessed in the memory of the server by the load balancer withoutinvolving a processor of the at least one server; determining, based onthe set of metrics associated with at least one server in the pluralityof servers, if the service request is to be sent to the at least oneserver; and sending the service request to the at least one server basedon determining that the service request is to be sent to the at leastone sever.
 10. The information processing system of claim 9, wherein theaccessing comprises: performing one or more remote direct memory accessoperations on a memory of the at least one server comprising the sharedmetrics array.
 11. The information processing system of claim 9, whereinthe accessing comprises: identifying a portion of the shared metricsarray associated with the at least one server; and analyzing the set ofmetrics associated with the at least one server.
 12. The informationprocessing system of claim 9, wherein the shared metrics array comprisesa plurality of slots, wherein each slot in the plurality of slots isassociated with one of the plurality of servers and comprises the set ofmetrics for the one of the plurality of servers.
 13. The informationprocessing system of claim 12, wherein each slot in the plurality ofslots further comprises at least one of: a timestamp associated with amost recent update to set of metrics stored within the slot; anidentifier associated with the server associated with the slot; and aset of connection information for the server associated with the slot.14. A computer program storage product for load balancing servicerequests across one or more servers, the computer program storageproduct comprising a non-transitory storage medium readable storinginstructions for execution by an information processing system forperforming a method comprising: accessing, by the information processingsystem in response to obtaining a service request, a shared metricsarray stored in memory of at least one server of a plurality of serversin a service cluster, where the information processing system comprisesthe service request and is external to the service cluster, and whereeach server in the plurality of servers comprises at least one servicefor satisfying the service request, the shared metrics array beingaccessible at the server by each of the plurality of servers, whereinthe shared metrics array comprises a set of metrics for each of theplurality of servers, and wherein each of the plurality of serverscomprises one or more services, the shared metrics array being directlyaccessed in the memory of the server by the information processingsystem without involving a processor of the at least one server;determining, based on the set of metrics associated with at least oneserver in the plurality of servers, if the service request is to be sentto the at least one server; and sending the service request to the atleast one server based on determining that the service request is to besent to the at least one sever.
 15. The computer program storage productof claim 14, wherein the accessing comprises: performing one or moreremote direct memory access operations on a memory of the at least oneserver comprising the shared metrics array.
 16. The computer programstorage product of claim 14, wherein the accessing comprises:identifying a portion of the shared metrics array associated with the atleast one server; and analyzing the set of metrics associated with theat least one server.
 17. The computer program storage product of claim14, wherein the method further comprises: based determining that theservice request is not to be sent to the at least one server; selectingat least one additional server from the plurality of servers; andsending the service request to the at least one additional server basedon the set of metrics associated with the at least one additionalserver.
 18. The computer program storage product of claim 14, whereinthe shared metrics array comprises a plurality of slots, wherein eachslot in the plurality of slots is associated with one of the pluralityof servers and comprises the set of metrics for the one of the pluralityof servers.
 19. The computer program storage product of claim 18, agiven slot in the plurality of slots is updatable only by its associatedserver in the plurality of servers.
 20. The computer program storageproduct of claim 18, wherein each slot in the plurality of slots furthercomprises at least one of: a timestamp associated with a most recentupdate to set of metrics stored within the slot; an identifierassociated with the server associated with the slot; and a set ofconnection information for the server associated with the slot.